Go – Function Basics
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Go Recursion – Solve Problems with Self-Calling Functions (2025 Guide)

Introduction – What Is Recursion in Go?

Recursion is a programming technique where a function calls itself to solve smaller instances of a problem until reaching a base case. In Go, recursion is commonly used for tasks like factorials, Fibonacci numbers, tree traversal, and other divide-and-conquer algorithms.

In this section, you’ll learn:

  • How recursion works in Go with examples
  • The difference between base case and recursive case
  • Practical recursive functions like factorial and Fibonacci
  • When to use recursion vs loops
  • Common pitfalls and optimization tips

Basic Recursive Function Syntax

func recurse() {
    // base case
    // recursive call
}

Key Concepts:

  • Base Case: The condition that stops recursion
  • Recursive Case: The function calls itself with a smaller input

Example – Recursive Factorial Function

func factorial(n int) int {
    if n == 0 {
        return 1 // base case
    }
    return n * factorial(n-1) // recursive case
}

func main() {
    fmt.Println(factorial(5))
}

Output:

120

factorial(5) calls factorial(4), factorial(3), … until factorial(0) returns 1.


Example – Recursive Fibonacci Function

func fibonacci(n int) int {
    if n <= 1 {
        return n
    }
    return fibonacci(n-1) + fibonacci(n-2)
}

func main() {
    fmt.Println(fibonacci(6)) // Output: 8
}

Output:

8

Recursively adds fibonacci(n-1) and fibonacci(n-2).

This version is not optimized—it recalculates the same values repeatedly. Use memoization for performance.


Example – Tree Traversal Using Recursion

type Node struct {
    value int
    left  *Node
    right *Node
}

func inOrder(n *Node) {
    if n == nil {
        return
    }
    inOrder(n.left)
    fmt.Println(n.value)
    inOrder(n.right)
}

This recursively prints the values of a binary tree in in-order traversal.


Recursion vs Loop in Go

FeatureRecursionLoop
Suited forTree, graph, divide & conquerLinear, countable operations
Base case needed? Yes No
Risk of stack overflow If depth is too large Stack-safe
Easier forNested or hierarchical problemsFlat, repeated operations

Common Pitfalls & Best Practices

MistakeFix
Missing base caseAlways include a clear stopping condition
Stack overflowAvoid deep recursion without limits
Recalculating subproblemsUse memoization to cache results
Prefer recursion?Only when it fits naturally

In Go, prefer loops over recursion when performance and readability matter.


Best Practices

  • Always define a base case to prevent infinite recursion
  • Use recursion when the problem is naturally recursive (trees, graphs)
  • Avoid recursion in performance-sensitive tight loops (e.g., Fibonacci without memoization)
  • Consider tail-recursion or loop conversion where possible

Summary – Recap & Next Steps

Recursion in Go is a powerful problem-solving tool, especially for problems involving self-similarity or hierarchical structures. With proper use of base cases and depth control, you can solve complex tasks with clean code.

Key Takeaways:

  • Recursive functions call themselves with smaller input
  • Base cases are critical to stop the recursion
  • Recursion is best suited for trees, graphs, or divide-and-conquer tasks
  • Optimize with memoization or prefer loops where recursion is inefficient

Next: Explore Go Variadic Functions to accept variable-length arguments in function calls.


FAQs – Go Recursion

What is recursion in Go?
A function that calls itself repeatedly until a base condition is met.

Is recursion supported natively in Go?
Yes. Go fully supports recursion just like other modern languages.

What happens if I forget the base case in recursion?
The program will run indefinitely until it causes a stack overflow.

Is recursion more efficient than a loop?
Not always. Loops are often more efficient in Go due to better stack management.

Can Go optimize tail recursion?
No. Go does not perform tail-call optimization. Use loops for better stack performance.


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